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Hannes Hettling

Dr. H. (Hannes) Hettling, Research fellow - Endless forms


Email: hannes.hettling@naturalis.nl
Phone: +31 (0)71-751 9368
Room number: 4.35, Darwinweg 2

As a trained Bioinformatician, I am interested in quantitative evolutionary biology and phylogenetics. I enjoy developing software and methods for data analysis and phylogenetic tree inference.


After completing my Ph.D. in computational Systems Biology at the Vrije Universiteit Amsterdam, I joined the Naturalis Biodiversity Center to work as a Bioinformatics research fellow in close collaboration with the University of Gothenburg, Sweden.


Research interest

My main interest is to tackle the challenges of infering large phylogenetic trees from molecular sequencing data. In my current project, I am working (among others) on a software pipeline for automatic generation of large dated phylogenies using publicly available data resources.


phylogenetics, data analysis, computational biology, data mining

Current research topics

The SUPERSMART pipeline for large-scale phylogenetic inference.


The Antonelli Lab - University of Gothenburg, Sweden.   



Not applicable.

Available student projects



Journals SCI, peer-reviewed

Bennett D.J., Hettling H., Silvestro D., Zizka A., Bacon C.D., Faurby S., Vos R.A., Antonelli A. 2018. phylotaR: An Automated Pipeline for Retrieving Orthologous DNA Sequences from GenBank in R. Life (Basel, Switzerland) 8: 20.
Go to website (DOI)

Bennett D., Hettling H., Silvestro D., Vos R.A., Antonelli A. 2018. restez: Create and Query a Local Copy of GenBank in R. Journal of Open Source Software 3: 1102.
Go to website (DOI)


Journals SCI, peer-reviewed

Antonelli A., Hettling H., Condamine F.L., Vos K., Nilsson R.H., Sanderson M.J., Sauquet H., Scharn R., Silvestro D., Töpel M., Bacon C.D., Oxelman B., Vos R.A. 2017. Towards a self-updating platform for estimating rates of speciation and migration, ages, and relationships of taxa (SUPERSMART). Systematic Biology 66: 152-166.
Go to website (DOI)


Journals SCI, peer-reviewed

Hardisty A.R., Bacall F., Beard N., Balcázar-Vargas M.-P., Balech B., Barcza Z., Bourlat S.J., Giovanni R. De, Jong Y. de, Leo F. De, Dobor L., Donvito G., Fellows D., Fernandez Guerra A., Ferreira N., Fetyukova Y., Fosso B., Giddy J., Goble C., Güntsch A., Haines R., Ernst V.H., Hettling H., Hidy D., Horváth F., Ittzés D., Ittzés P., Jones A., Kottmann R., Kulawik R., Leidenberger S., Lyytikäinen-Saarenmaa P., Mathew C., Morrison N., Nenadic A., Nieva de la Hidalga A., Obst M., Oostermeijer G., Paymal E., Pesole G., Pinto S., Poigné A., Quevedo Fernandez F., Santamaria M., Saarenmaa H., Sipos G., Sylla K.-H., Tähtinen M., Vicario S., Vos R.A., Williams A.R., Yilmaz P. 2016. BioVeL: a virtual laboratory for data analysis and modelling in biodiversity science and ecology. BMC Ecology 16: 49.
Go to website (DOI)


Journals SCI, peer-reviewed

Gavai A.K., Supandi F., Hettling H., Murrell P., Leunissen J.A.M., Beek J.H.G.M. 2015. Using bioconductor package BiGGR for metabolic flux estimation based on gene expression changes in brain. PLOS ONE 10: e0119016.
Go to website (URI)


Journals non-SCI, peer-reviewed

Vos R.A., Biserkov J.V., Balech B., Beard N., Blissett M., Brenninkmeijer C., Dooren T. van, Eades D., Gosline G., Groom Q.J., Hamann T.D., Hettling H., Hoehndorf R., Holleman A., Hovenkamp P., Kelbert P., King D., Kirkup D., Lammers Y., DeMeulemeester T., Mietchen D., Miller J.A., Mounce R., Nicolson N., Page R., Pawlik A., Pereira S., Penev L., Richards K., Sautter G., Shorthouse D.P., Tähtinen M., Weiland C., Williams A.R., Sierra S. 2014. Enriched biodiversity data as a resource and service. Biodiversity Data Journal 2: 1-15.
Go to website (URI)


Journals non-SCI, peer-reviewed

Hettling H., Alders D.J., Heringa J., Binsl T.W., Groeneveld A.J., Beek J.H.G.M. van 2013. Computational estimation of tricarboxylic acid cycle fluxes using noisy NMR data from cardiac biopsies. BMC Systems Biology 7: 82.


Journals SCI, peer-reviewed

Beek J.H.G.M. van, Supandi F., Gavai A.K., Graaf A.A. de, Binsl T.W., Hettling H. 2011. Simulating the physiology of athletes during endurance sports events: modelling human energy conversion and metabolism. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 369: 4295-4315.

Hettling H., Beek J.H.G.M. van 2011. Analyzing the functional properties of the creatine kinase system with multiscale ‘sloppy’ modeling. PLoS Computational Biology 7: e1002130.


Journals SCI, peer-reviewed

Hettling H., Heringa J., Beek J.H.G.M. van 2010. Analysis of the functional properties of the creatine kinase system using a multiscale ‘sloppy’ modeling approach. BMC Bioinformatics 11: O9.

Beek J.H.G.M. van, Binsl T.W., Hettling H., Heringa J. 2010. CGHnormaliter: a bioconductor package for normalization of array CGH data with many CNAs. Bioinformatics 26: 1366-1367.

Journals non-SCI, peer-reviewed

Beek J.H.G.M. van, Alders D.J., Hettling H., Binsl T.W. 2010. 112 In vivo measurement of heterogeneous mitochondrial metabolic fluxes in small myocardial regions. Mitochondrion 10: 231.


Journals SCI, peer-reviewed

Beek J.H.G.M. van, Hauschild A., Hettling H., Binsl T.W. 2009. Robust modelling, measurement and analysis of human and animal metabolic systems. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 367: 1971-1992.

Journals non-SCI, peer-reviewed

Beek J.H.G.M. van, Binsl T.W., Hettling H., Pirovano W., Heringa J. 2009. CGHnormaliter: an iterative strategy to enhance normalization of array CGH data with imbalanced aberrations. BMC Genomics 10: 401.